Conference item
Rethinking the proposition of privacy engineering
- Abstract:
- The field of privacy engineering proposes a methodological framework for designing privacy-protecting information systems. Recognising that the utilisation of privacy-enhancing techniques for data storage and analysis does not address the entire scope of individual privacy, privacy engineering incorporates influences from user sentiment, legal norms and risk analysis in order to provide a holistic approach. Framed by related design principles, such as 'Privacy-by-Design', privacy engineering purports to provide a practical, deployable set of methods by which to achieve such a holistic outcome. Yet, despite this aim, there have been difficulties in adequately articulating the value proposition of privacy engineering. Without being able to adequately define privacy or map its contours, any proposed methodology or framework will be difficult to implement in practice, if not self-defeating. This paper identifies and examines the assumptions that underpin privacy engineering, linking them to shortcomings and open questions. Further, we explore possible research avenues that may give rise to alternative frameworks.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 538.5KB, Terms of use)
-
- Publisher copy:
- 10.1145/3285002.3285006
Authors
+ University College, University of Oxford
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- Funding agency for:
- Ceross, A
- Grant:
- EP/P00881X/1
+ Engineerinng and Physical Sciences Research Council
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- Funding agency for:
- Ceross, A
- Grant:
- EP/P00881X/1
- Publisher:
- Association for Computing Machinery
- Host title:
- NSPW '18 Proceedings of the New Security Paradigms Workshop
- Journal:
- Proceedings of the 2018 New Security Paradigms Workshop (NSPW 2018 More from this journal
- Pages:
- 89-102
- Publication date:
- 2018-08-28
- Acceptance date:
- 2018-06-11
- DOI:
- ISBN:
- 9781450365970
- Pubs id:
-
pubs:858749
- UUID:
-
uuid:f59a9106-155c-43c2-b3da-dc986240ad03
- Local pid:
-
pubs:858749
- Source identifiers:
-
858749
- Deposit date:
-
2018-06-21
- ARK identifier:
Terms of use
- Copyright holder:
- Association for Computing Machinery
- Copyright date:
- 2018
- Notes:
- Copyright © 2018 Association for Computing Machinery. This is the accepted manuscript version of the paper. The final version is available online from ACM at: https://doi.org/10.1145/3285002.3285006
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